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IIoT: An evolution-to a smart manufacturing enterprise

The Industrial Internet of Things (IIoT) is not about
ripping out current automation systems in order to
replace them with new ones. The potential lies in the
ability to link automation systems with enterprise
planning, scheduling and product lifecycle systems. This
paper analyses how the linkage can be implemented
across the complete enterprise value chain in order to
enable greater business control. Experts also offer
perspectives regarding key aspects of IIoT deployment.
Learn more...
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IIoT: An evolution-to a smart manufacturing enterprise

1.
The Industrial Internet of Things:
An Evolution to a Smart
Manufacturing Enterprise
by John Conway
Executive summary
The Industrial Internet of Things (IIoT) is not about
ripping out current automation systems in order to
replace them with new ones. The potential lies in the
ability to link automation systems with enterprise
planning, scheduling and product lifecycle systems. This
paper analyses how the linkage can be implemented
across the complete enterprise value chain in order to
enable greater business control. Experts also offer
perspectives regarding key aspects of IIoT deployment.
998-2095-10-16-15BR0

2.
The Industrial Internet of Things: An Evolution to a Smart Connected Enterprise
Schneider Electric White Paper Revision 0 Page 2
The Industrial Internet of Things (IIoT) is often presented as a revolution that is changing the
face of industry in a profound manner. In reality, it is an evolution that has its origins in
technologies and functionalities developed by visionary automation suppliers more than 15
years ago. As the necessary global standards mature, it may well take another 15 years to
realise the full potential of IIoT. Over this period of time the changes to the industry will be far
reaching. The good news is that end users and machine builders can now leverage their
existing investments in technology and people while taking advantage of available new IIoT
technologies. Introducing IIoT solutions using a “wrap & re-use” approach, rather than a “rip &
replace” approach will enable greater business control. In addition, this measured approach
will drive the evolution towards a smart manufacturing enterprise that is more efficient, safer,
and sustainable.
The emergence of the IIoT megatrend has created both hope and confusion among
stakeholders responsible for operating industrial plants. Much of the early hype is focused on
the impact of technological advancements on existing automation platforms.
However, one of the challenges in understanding the potential of IIoT is the very large scope
of applications. In the area of smart enterprise control, for example, we will see self
organizing machines and assets that enable mass customization and lot sizes of one. In the
realm of asset performance, the collection and analysis of data from increasing numbers of
cost-effective and intelligent sensors will increase business performance and asset uptime. A
new generation of “augmented” workers will leverage cutting edge technologies, including
mobile devices and augmented reality. With easier access to information across the
enterprise, their work becomes simplified and production systems grow more profitable.
Some of these changes can be implemented in the short to medium term, others will require
a gradual evolution with end users and OEMs incrementally adding functionality to their
existing legacy systems as new international IIoT standards are established.
The IIoT vision of the world is one where smart connected assets (the things) operate as part
of a larger system or systems of systems that make up the smart manufacturing enterprise.
The “things” possess varying levels of intelligent functionality, ranging from simple sensing
and actuating, to control, optimisation and full autonomous operation.
The smart manufacturing enterprise is made up of smart machines, plants and operations all
of which have higher levels of intelligence embedded at the core. The linked systems are
based on open and standard Internet and cloud technologies that enable secure access to
devices and information. This allows “big data” to be processed with new, advanced analytics
tools and for mobile technologies to drive greater business value. This, in turn, enables
improvements to efficiency and profitability, increased cyber security and innovation and
better management of safety, performance with reduced CO2 emissions impact.
While the long term impact of IIoT is at times difficult to predict, three distinct operational
environments will set the stage for the smart manufacturing enterprise to emerge.
• Smart Enterprise Control – IIoT technologies will enable tight integration of smart
connected machines and smart connected manufacturing assets with the wider
enterprise. This will facilitate more flexible and efficient, and hence profitable,
manufacturing. Smart enterprise control can be viewed as a mid-to-long-term trend. It is
complex to implement and will require the creation of new standards to enable the
convergence of IT and OT systems.
• Asset Performance Management – Deployment of cost effective wireless sensors,
easy cloud connectivity (including WAN) and data analytics, will improve asset
Smart
Manufacturing
Enterprise
Definition
Introduction

3.
The Industrial Internet of Things: An Evolution to a Smart Connected Enterprise
Schneider Electric White Paper Revision 0 Page 3
performance. These tools allow data to be easily gathered from the field and converted
into actionable information in real time. This will result in better business decisions and
forward-looking decision making processes.
• Augmented Operators – Future employees will use mobile devices, data analytics,
augmented reality and transparent connectivity to increase productivity. As fewer
skilled workers are left behind to man core operations due to a rapid increase in baby-
boomer retirement, younger replacement plant workers will need information at their
fingertips. That information will be delivered in a real-time format that is familiar to
them. Thus the plant evolves to be more user-centric and less machine-centric.
While these three areas are closely related and share many inter-dependencies, they also
have differences. For example the time scales on which they can be implemented and the
kind of automation market segment that they address are not the same.
There are two other areas, collaborative robotics and 3D printing, which are also pertinent to
the discussion surrounding IIoT, but these are not discussed in this paper as they are specific
technologies that cannot be applied to all manufacturing enterprises.
Smart Enterprise Control
One of the biggest potential benefits of next generation IIoT systems is the breakdown of
enterprise silos. The technologies will allow for closer integration of production systems and
ERP systems, Product Lifecycle Management (PLM) systems, Supply Chain Management
and Customer Relationship Management (CRM) systems (see Figure 1). Today these
systems are managed somewhat independently of each other, which prohibits a holistic view
of the enterprise. It is believed such a holistic approach could facilitate an enormous
efficiency gain of up to 26 per cent
1
for enterprises.
Smart enterprise control does not mean replacing current automation systems with
completely new systems. Instead, it implies the connection of current automation systems
with enterprise, lifecycle and value chain systems. This optimises the entire manufacturing
enterprise and enables a much greater degree of business control.
1
McKinsey & Company Industry 4.0 - How to navigate digitization of the manufacturing sector
Figure 1
Holistic enterprise control
breaks down enterprise silos
and facilitates better
business control.

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The Industrial Internet of Things: An Evolution to a Smart Connected Enterprise
Schneider Electric White Paper Revision 0 Page 4
Tighter integration will allow enterprises to not only be more efficient, but also more profitable
thanks to greater flexibility and responsiveness to volatile market conditions. The notion of
control will expand from the real-time control of a physical parameter, to the right-time control
of the whole business, including both physical and non-physical parameters. Benefits will
include the ability to enhance protection against cyber threats, more innovation, and the
ability to better manage safety, performance and environmental impact.
Examples of smart enterprise control include the following: mass customisation and lot sizes
of one, reducing the size of product recalls, detection of defective products earlier in the
manufacturing process and modification of product design to eliminate root causes,
modification of production planning based on weather forecasts, modification of production
plan/recipes based on the spot price of raw materials.
Asset Performance
Asset performance management applications such as energy management and predictive
maintenance are not new to industry, but have had limited uptake due to the cost of
implementation. The costs of physical connectivity (the cost of cabling to the sensors) and
logical connectivity (integration with existing systems) have been prohibitive. Wireless IP
connectivity and cloud-based architectures now overcome these cost barriers. In addition, a
new generation of simple, small and low cost sensors is emerging; As a result, next
generation IIoT systems will deliver innovative solutions in the area of asset performance
(see Figure 2).
Consider the example of condition-based monitoring/predictive maintenance. Much money is
wasted maintaining equipment that doesn’t require maintenance, or by neglecting equipment
that subsequently fails and causes unanticipated production downtime. Solutions such as
condition-based monitoring do exist today, but uptake has been limited by cost. Next
generation IIoT systems promise to significantly reduce implementation costs for such
solutions.
Augmented Operator
The use of mobile Human Machine Interface (HMI) technologies such as smart-phones,
tablets and wearables, combined with IP-access to data and information (analytics and
augmented reality) will transform the way operators work. Portable wireless devices will
Figure 2
Asset performance
accelerates the adoption of
new performance
management applications
leveraging big data and
analytics, and cost-effective
wireless technologies.
“Holistic enterprise control
will be achieved through a
‘wrap & re-use’ approach
rather than a ‘rip &
replace’ approach.”

5.
The Industrial Internet of Things: An Evolution to a Smart Connected Enterprise
Schneider Electric White Paper Revision 0 Page 5
expand their capabilities and technologies such as dynamic QR codes will improve the
operator experience and render the “augmented” operator more productive (see Figure 3).
Today, operators only have access to information from automation systems. Tomorrow,
augmented operators will access information from all of the needed enterprise systems and
will manage not just process performance/efficiency, but also process profitability.
Several barriers will need to be overcome before next generation IIoT systems are widely
adopted across manufacturing industries. These include the establishment of industry
standards around IIoT, cyber security protection, and workforce adaptation to new sets of
skills.
Standardisation
Standards are required to allow smart connected products, machines and assets to interact in
a transparent fashion. This goes beyond the simple communication protocols, and involves
the creation of standard semantics and mechanisms that will allow smart devices to discover
each other and interoperate. Some standards, such as PackML, do exist in this area, but they
are incomplete and do not cover all aspects of manufacturing. The Industry 4.0 and the
Industrial Internet Consortium initiatives are currently addressing the question of
standardisation.
Cyber security
The advent of the IIoT is accelerating the need for cyber security in industrial control
systems. The complexity of IIoT will mean that cyber security must be designed into the
components that make up the automation system.
The adoption of industrial security standards with certification will be essential to the
advancement of IIoT because it will ensure the security not just of individual assets but also
of the larger systems and systems of systems. These certifications will play a role similar to
those which occur in the realm of safety certifications. Adherence to the certification means
that the elements of a system hold the key security building blocks. The elements are
combined in a secure way by security certified teams and are operated as a secure system
by security trained operators.
Figure 3
Augmented operators
are more productive
because they receive
the right information at
the right time.
Barriers to
adoption
“The adoption of industrial
security standards with
certification is essential to
the advancement of IIoT.”
PLM
CRML1
L2
L3
L4
Sensors/Actuators
Control
Discrete/Hybrid/Continuous
Manufacturing
Operations Mgt
ERP Product Life Cycle
Mgt
SCM
Supply Chain Mgt
Customer Relationship
Mgt

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The key to security certification is consistency and applicability. Worldwide, the IEC62443
series of security standards covers all elements of security from product development through
to product features, system features, delivery and operation. It is important to note that while
today some independent bodies offer certification to IEC62443, IEC itself has not yet
endorsed any of these bodies for IEC62443 certification.
Complementary to IEC62443 security standards, existing industrial standards are also
evolving to be more secure. DNP3 has evolved to DNPV5 to add security, OPCUA offers
significant security enhancements, Modbus is evolving to Modbus Secure, EtherNET/IP is
becoming EtherNET/IP Secure. In addition many IIoT systems are adopting security features
derived from existing IT standards such as HTTPS, certificates, and encrypted/authenticated
protocols.
Worker competencies
The skill-sets required to design and operate an IIoT-based system are somewhat different
from those needed to run a classical automation system (see Figure 4). A significant amount
of re-training will be required for existing operators and maintenance staff to manage such
systems. The good news is that the IIoT systems will use technologies that are familiar in
everyday life, and the new generation of young operators will have no problems adapting to
this new approach. The main challenge for automation suppliers will be to design and supply
diagnostics/debug tools that can rapidly identify the root cause of problems. This will ensure
that a malfunctioning or downed system can be restored quickly.
Figure 4
Many new skills will be
required to design and
operate IIoT systems.

7.
The Industrial Internet of Things: An Evolution to a Smart Connected Enterprise
Schneider Electric White Paper Revision 0 Page 7
Information driven architectures
As smart manufacturing enterprises start implementing smart enterprise control and asset
performance systems managed by augmented operators, automation vendors will respond by
implementing IIoT at all levels of the automation hierarchy. This will allow easy integration
with next generation IIoT systems. In addition, with the increasing power of embedded
electronics, connected intelligence will migrate down to the lower levels of the automation
hierarchy – to the control level and to the sensors and actuators. As a result, operations
technology (OT) systems will merge with information technology (IT) systems and the
automation hierarchy will evolve to be a much flatter and more information-driven
architecture. Since the future implications of this are still unclear, the technologies and
architectures employed must be flexible, adaptable to change and capable of integrating with
legacy systems. The monolithic, single-source, hierarchical approaches and architectures of
the past will not work in the future.
The information-driven topology is shown below in Figure 5.
The architecture consists of two distinct layers. Information flow across both layers will be
transparent using semantics and discovery mechanisms based on industry standards. Both
layers are explained below:
1. A time-sensitive layer for real-time deterministic control. This layer is often referred
to as “fog” or “edge”. However using the term “time-sensitive IP-based” for this layer
underlines the fact that the technologies included in this layer are fundamentally the
same IIoT technologies used in the enterprise cloud layer, but are optimised for real-
time deterministic communications.
The OT devices that comprise this time sensitive layer (sensors, actuators and
controllers) will be cloud-ready and capable of interfacing transparently with the IT
business systems of the second layer. Those same devices will also have a high
degree of intelligence. Consider the example of control valves with embedded
temperature, pressure and acoustic sensors. They are able to operate autonomously
using set points from the enterprise, determining their own needs for preventive
maintenance, and informing the maintenance department of their condition in a timely
manner.
2. A cloud enterprise layer where enterprise systems (ERP, MOM, PLM, SCM, CRM,
etc) and next-generation functions including asset management and energy
Figure 5
The information-driven
automation architecture
“Monolithic, single-source,
hierarchical approaches
and architectures of the
past will no longer be
viable in the age of IIoT.”
Impact on
automation
architectures

8.
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Schneider Electric White Paper Revision 0 Page 8
management interoperate with each other and with the time-sensitive cloud-ready
systems.
The use of the term cloud above refers to the technologies used, rather than the physical
location of the infrastructure. There are many reasons to believe that, in the industry
automation business, “on-premise” clouds (commonly referred to as “edge”), will be the most
widely used architecture.
Centralised versus distributed control
The arguments for highly centralised redundant control systems versus highly distributed
control systems have gone on for many years. Proponents of each architecture fiercely
defend their position with valid arguments.
The advent of IIoT does not resolve this long-standing debate. On the one hand, the use of
cost-effective embedded electronics in field devices argues for more distribution of
intelligence and control. On the other hand, the high speed IP-connectivity of field devices
enables a more centralised architecture where all the sensors and actuators are connected to
a highly redundant and powerful multi-core processor located in a secure on-premise data
centre.
Today an application is programmed with a particular hardware target in mind, for example a
PLC. Tomorrow, an application will be programmed independently of the underlying
automation hardware, and the system will distribute the application transparently to the
hardware, configuring all communication mechanisms automatically. This approach will allow
users to choose either a highly centralised or distributed architecture, or a hybrid approach
based on their specific requirements and concerns. A Distributed Control Standard (IEC
61499) exists that will facilitate this work and which can be used as the basis for an IIoT
distributed control standard.
The distribution of intelligence into the field will allow smart connected products and smart
connected machines to publish important information in a standardised format. Intelligent
brokers will make this information available in a transparent manner to the systems and
applications that require it. This approach will overcome one of today’s current challenges:
the location of information is unknown and therefore cannot be discovered or exploited
without custom programming.
Networked automation architectures
Networks will see an exponential increase in the number of smart connected devices. These
devices will exploit a time-sensitive IIoT/Ethernet backbone to interoperate with each other
and with devices residing in other enterprise systems,
An example of the sheer number of connected devices can be seen at the Torresol Energy
Gemasolar solar power plant where 4000 Schneider Electric PLCs/drives are connected via
Ethernet to control the displacement of solar mirrors. The large number of networked devices
presented many new challenges not only in the area of network management and
performance but also in the area of managing the overall configuration of the distributed
control system and its application software.
Implementing such large networked systems with today’s classical automation techniques is
complex. Tomorrow’s IIoT-based automation systems will require a new approach to simplify
the design, the management, and the maintenance of networked automation architectures.

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IIoT is often described as a revolution that will change life as we know it. In the areas of
consumer goods, building management and others there is some truth to this. However,
across industry, IIoT will be applied more slowly as different sectors of the industrial markets
evolve their specific needs and address their unique challenges.
Technological elements leading the IIoT evolution
By Eric Farrugia, VP Strategic Marketing, Industrial Controls & Drives
IIoT is blurring the boundaries between physical and virtual objects. This is giving way to
more flexible models of accessing process and machine data – bypassing rigid automation
architectures and accessing user-friendly, mobile systems based on Internet standards. While
generating and collecting data is an important aspect of IIoT, this alone will not enable
manufacturers to realize the full benefit of IIoT – there are other components to consider:
1. Smart connected devices that are IIoT ready will deliver an “advanced sensing
system” that generates information with the first level of data analysis completed by
the device itself
2. An edge gateway to aggregate data, display information and connect to the cloud for
advanced analytics
3. Applications and services to further analyse data and put it into context to help reach
business goals
4. An open and collaborative environment to allow partners to develop on a common
platform
Delivering smart connected devices that are IIoT ready means embedding Internet
technologies like WIFI and web services natively into those devices. For example, Variable
Speed Drives are essential to industrial processes by way of providing information on motor
use and other devices like sensors and relays provide information on the device lifecycle.
Embedded digital services also become critical to support process optimisation. For example
the new series of Altivar Process drives with built in web technology standards, Ethernet
connectivity, intelligence and asset management or energy management features deliver
additional contextual information, including real time events, alarms, drifts, and historical
data.
An edge gateway will aggregate data collected from various sources and deliver real-time
business information to the right people at the right time. This is the key interface between
the Internet world and the process (the things). It also facilitates value-added services
independent of the control system. Supporting this vision is the new Magelis GTU HMI which
offers the flexibility of combining a CPU box with a choice of display, including a Wireless
LAN enabled display. The edge gateway ensures a high level of performance and
connectivity to address the critical needs of the IIoT platform.
Digital applications and services are critical to end users achieving the business performance
gains promised by IIoT. Simple data collection must be extended to include analytics that
deliver pertinent and valuable business information. Some examples of such applications and
services include installation optimisation, asset management and protection, condition based
monitoring, augmented reality applications and OEE calculation, among others.
A platform built on an open and collaborative environment will allow selected partners to
develop specific applications that extend offerings and reach to help deliver the promise of
IIoT. A consistent development environment with governance and processes will enable easy
integration of IIoT platforms.
Expert
perspectives
“Delivering smart
connected devices that
are IIoT ready means
embedding Internet
technologies like WIFI and
web services natively into
those devices.”

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Schneider Electric White Paper Revision 0 Page 10
Measurement and the art of “simply-complex”
By Matthew Carrara, VP, Field Devices, and Michael Davis, Senior Program Manager, Field
Devices
The technical capacity of the Industrial Internet of Things will provide the opportunity to
redeploy the building blocks of industrial processing to measurement, control and
connectivity. While these three building blocks iteratively rely on each other for balance, it all
starts with measurement – which is the catalyst for process optimisation and improvement.
IIoT will not only rely on this historically fundamental component of processing, but will reach
deeper and expect more. Measurements of the future will capitalise on technologies that will
significantly reduce size and cost, increase computing storage and power, and eliminate
wired connectivity (for power and communications). These changes will result in a game-
changing increase in the volume of applied measurement. With extremely low cost sensors
capable of real-time and predictive data connectivity, stakeholders will realise the value of
employing massive numbers of measuring devices for control and process optimisation.
Analogous to all living systems, where sensing is elegantly performed at the molecular level, IIoT
sensors will evolve to single performance tasks. In living systems, each biologic sensor is a
unique molecular configuration designed to measure a specific parameter (pressure, insulin, pH,
temperature, etc.). There may be thousands of similar or different biologic sensors in a single
microscopic cell. In a similar way, tomorrow’s IIoT sensing elements will be tiny and comprised of
very few unique parts while embedding far more data manipulating intelligence, passing along
only relevant information to control cyber-physical systems (aka smart-connected assets).
Today's process sensors are marketed as 'smart' or 'intelligent', but while technical
advancements have allowed for increasing embedded intelligence, the resulting sensors have
become large and expensive, thus self-limiting volume deployment. Market purchases of sensing
devices are not limited by the desire for less information but by the high cost of deployment (the
sensor plus the installation cost of cabling). The market for measurement devices will explode in
volume for the supplier that can deliver the true capability of IIoT using simple wireless sensors.
By driving simplicity to the fundamental components (measurement), driving differentiating
analytics to the control level, and linking them using wireless connectivity and cloud-based
architectures, there will be a directional shift in the Industrial Automation and Control model –
one that can be defined as “simply complex”, where simple measurements plus complex
analytics equate to customer value.
Capitalizing on IIoT opportunities will require a fundamental shift in culture, thinking,
architecture, strategy and investment. With many of the IIoT technologies already available,
and simple sensor designs currently under review, the journey to a smart evolution has
begun.
SMART Machines: What they are and how they contribute to the
future of the industry
By Dr. Rainer Beudert, Marketing Director, Machine Solutions.
The smart machine concept has a number of key enablers (from the technology perspective)
and drivers (from the end user and market perspective). The combination of both will lead to
machines that are safe, secure, self-aware, flexible and capable of meeting demands from
both end users and consumers. The integration of internet connected devices, adoption of
automated components and processes, and access to real-time production data, will
empower end users to migrate to smarter machines. As production benefits in terms of cost
reduction, reduced downtime, quality, and throughput, are achieved and competitive
advantage gained, so the drive to smarter machines will quicken and expand into a broader
spectrum of industries.
“The market for
measurement devices will
explode in volume for the
supplier that can deliver
the true capability of IIoT
using simple wireless
sensors.”

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Key characteristics of smart machines include the following:
• Self-awareness – Any deviation from set parameters will be identified by the smart
machine and communicated to the machine operator. Machines at the forefront of
development will use sensors with embedded intelligence to distribute and automate
decision making on the factory floor.
• Plug & play – Any new smart machines will need to be compatible with the existing
installations or machinery from multiple OEMs; End users want devices that can be
installed within a short timeframe. Integration into the rest of the system must be easy.
• Safety & cyber security – With security built into their fundamental designs, smart
machines will improve safety of operators and minimize the security risk of increased
networking.
• Connectivity – Smart machines will connect directly to the broader (IP-based)
network. This enables data sharing and production planning, which goes far beyond
the capabilities of traditional standalone machinery and automation. Smart machines
will bridge the IT / OT gap, making available production data that can be used in
numerous management settings (e.g., stock control, operator scheduling, maintenance,
energy management, and product replacement).
Major trends that support the proliferation of smart machines include the acceptance of
mobile devices to manage core business functions, and the ability to harness and interpret
the mountains of data that are being captured by the smart devices.
• Mobile devices – Mobile technologies, which are experiencing rapid growth within the
industry (see Figure 6), now free operations personnel from needing to be in close
proximity to a machine in order to monitor or manage performance. Now, machine
engineers can diagnose problems and offer guidance remotely. This cuts costs and
also speeds-up solution implementation.
• Data Management – As sensors and other networkable components are added to
machinery, huge amounts of production data are being generated. Even with relatively
simple applications, this could easily lead to data overload and the inability to use
production data to support real time decision making. Smart machines must have some
level of intelligence to assess data quickly and in a decentralized fashion. Routing all
data to a central control for analysis will quickly lead to delays, and is an un-scalable
Figure 6
Global market
projections for industrial
mobile applications
(courtesy of IHS)

12.
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structure. Having sensors, components and machinery with the intelligence to only
share data that falls within a set of pre-defined parameters, will lead to better data
management. Reducing the level of data shared with the broader network/community,
will speed up decision making and reduce backlogs (where critical information could be
delayed or missed altogether).
Evolving instrument communications in the IIoT age
By Peter Sherwin, Global Marketing Manager, Eurotherm by Schneider Electric
Control and data recording instrumentation
Over the past 15 years, quality requirements in regulated industries started to evolve and
influence the direction of instrumentation design and application. Digital data needed to be
captured in a secure format and an evolution of accuracy specifications required better levels
of repeatable process control. This affected the Aerospace and Automotive industries,
Pharmaceutical and Biotech industries (driven by the FDA) and now is starting to impact the
Food & Beverage industry through the Food Safety Modernization Act (FSMA).
Both early recording devices and more advanced devices that incorporated web servers and
Ethernet provided a full view of the instrument screen at any PC on the plant network. In
addition, security features were added to recording instruments to provide security
management and audit trail functionality. These smart recorders evolved into mini-
productivity stations enabling key information for thermocouple use, calibration tests and
machine maintenance to be scheduled directly on the device.
Quality standards dictated that direct communication links be established between the control
device and the recording instrument to eliminate errors created by conventional
retransmission methods. Ethernet-based Modbus TCP was used for device-to-device
communications to accurately transfer the control data to the process record.
For many years, instrument manufacturers have adopted the DIN standard for panel mounted
instruments, with standardized panel cut-out dimensions for controllers, recorders, and other
boxed mechanical devices. Devices since introduced that incorporated multi-loop control,
secure data-recording, integrated Ethernet and built-in web servers can now be seen as one
of the first range of IIoT mini-stations providing a necessary cost effective link between
sensors and the internet.
Current developments on this type of smart device will enable widespread use in both
regulated and non-regulated industries. Such a solution provides a cost-effective means for
generating advanced calculations (including Overall Equipment Effectiveness) as well as a
secure data link to the internet.
Power devices
Silicon controlled rectifier (SCR) power controllers (or thyristors) were developed to provide a
precise method of electrical switching in the control of power circuits. They were also
designed to overcome the limitations and lifetime issues of mechanical contactors. The SCR
technology is now being used to take an isolated controller and provide a system approach to
managed power demand.
A number of SCR devices will fire randomly at what could be many times per second. If the
units fire at the same time, then the load demand increases. By using power sequencing
across an Ethernet backbone to enable automated load balancing and load shedding
techniques it is possible to order the firing pattern and reduce the ultimate peak load demand.
These smart connected devices can be used for single or multi-zoned equipment and also
can be leveraged across multi-equipment cells. Communicating on an Ethernet backbone

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allows for future possibilities in automating the links between a utility supplier and the plant
floor so that efficient power demand scheduling can benefit both parties.
Workflows
Instrument-to- instrument communication has been a feature of IIoT development over the
past 10 years. It is recognized that to increase the value attributed to automation projects, the
links between the equipment, operator and supply and delivery chain need to be developed.
Workflow type applications are leading the charge in this area. Below are some examples:
• Production applications that embed regulatory IP into workflow solutions provide a link
between machines and decision makers in real-time. This ensures regulatory
requirements are constantly being achieved and that auto-alerts are raised for any
standards breach.
• Dairy applications that link to their remote supply chain using cloud technology and
regulatory parameters provide a control and data process to address all points in the
supply chain from cow to table.
• Calibration applications that facilitate easy regular equipment calibration checks. This is
a key requirement for many regulated industries. This can now be achieved with the
introduction of online services using cloud storage of calibration records. Inputs include
tablet entry and a link to secure files through QR codes from the instrument label (using
a Smartphone/tablet QR reader).
Driving business value for process control industries through
smart connected assets
By Don Clark, Senior Director, Industry Solutions, and Dr. Peter Martin VP Industry Solutions,
Process Automation
Automation systems and technologies exist to drive improved value for industrial operations and
businesses in a safe and environmentally responsible manner. New trends in automation should
be evaluated on two levels – the technological level and the functional level. The technological
level deals with the impact of technological advancements on the technology and topology of the
automation platform. The functional level deals with the incremental functionality that can be
delivered on the automation platform to improve operational and business value. The IIoT
movement provides significant transformation at both levels, with the net impact being a
significant increase in the value industrial companies derive from automation.
Most of the current fervour associated with IIoT has been at the first level. There are a number of
technologies including connectivity, networking, big and small data analytics, cloud computing,
fog computing, wireless communication, cyber physical systems and edge computing that are
gaining a high level of acceptance in the industrial sector. Independently these technologies are
promising. In combination, however, they offer an unprecedented opportunity. Together, these
technologies create an environment which removes many of the traditional technological
constraints imposed on automation systems. Automation systems designers now can design an
automation system from a clean slate.
Cost, speed, and size limitations of older technologies have led to automation architectures and
topologies being defined by the technological constraints. The result has been the development
of two different industrial operations topologies; the automation system topology and the
industrial operations topology. This has caused an increase in complexity in industrial operations
as personnel had to learn both topologies to effectively operate a facility.
With new levels of agility offered by IIoT, the topology of automation systems can be perfectly
matched to industrial topologies, drastically simplifying the application and operation of both.
“These technologies
create an environment
which removes many of
the traditional
technological constraints
imposed on automation
systems.”

14.
The Industrial Internet of Things: An Evolution to a Smart Connected Enterprise
Schneider Electric White Paper Revision 0 Page 14
These new automation systems topologies will be called natural topologies due to their natural
alignment to industrial operations. The expected result of this alignment will be the application of
automation systems to each asset and asset set in the industrial operation, from the simplest
piece of equipment through to process units or work cells, trains, areas, plants, fleets and
enterprises. This will lead to simplified environments with unified smart connected asset control
systems combined into smart industrial enterprise control systems. Under such a system,the
operation of each asset and asset set is controlled for optimal business results.
At the functional level, automation systems were originally developed to control processes in real
time. Most real-time process control implemented to date has been focused on improving the
efficiency of a process or machine, and not the operation as a whole. Although improving
efficiency is important, it is far from the only domain to which real-time control should be applied
in industrial operations. As the speed of industrial businesses has continually increased over the
past decade, managing industrial assets on a human, transactional schedule has proven to be
insufficient. Important industrial variables, such as profitability, safety risk, environmental risk,
reliability and security risk, that have traditionally been managed on a daily, weekly or monthly
schedule have now transitioned to real-time. Therefore, it is no longer possible to keep managing
them in the same way.
Real-time controls are needed to support these important business elements. Decisions
influenced by either manual or automatic, feedback or predictive controls need to be made fast
enough to positively impact the operation of a process. Real-time controls will need to be applied
to improve the efficiency, reliability, profitability, safety risks, environmental risks and security
risks for each asset and asset set in industrial enterprises. This will result in true asset
performance control which will then lead to optimal enterprise performance.